How does the "Lorem Ipsum" generator work?
Lorem ipsum generators don't typically use anything considered as AI. Usually they just store large pieces of text and select sections from it randomly - they are very simple. The main goal is to produce "nonsense" text that fills space but does not distract from issues of layout and design. The variations of it are usually just for fun, and like the original, are mostly simple generators which select strings of text from a core data source randomly and without using any AI techniques.

It is possible to build more sophisticated random text generators that work using data structures from Natural Language Processing (NLP). 

One popular and easy-to-code data structure is N-grams, which store the frequencies/probabilities of the Nth word given words 1 to N-1. E.g. a bigram structure can tell you all the possible words to come after "fish" e.g. "fish" =&gt; ["food" =&gt; 0.2, "swims" =&gt; 0.3, "and" =&gt; 0.4, "scale" =&gt; 0.1] To use that structure to generate text, use a random number generator to select a word based on looking up the Nth word's frequency, then shift the list of words being considered and repeat. 

A more recent text generating NLP model is recurrent neural networks (RNNs), which have a variety of designs. Popular right now are LSTM networks, and these are capable of some quite sophisticated generation, provided they are trained with enough data for long enough. The blog The Unreasonable Effectiveness of Recurrent Neural Networks by Andrej Karpathy has quite a few really interesting examples of using RNNs for text generation. In practice this works similarly to n-grams: Use the RNN to suggest probabilities for next word given words so far, choose one randomly, then feed back the generated word into the RNN and repeat.